A ( ) is the attribute in the supertype entity that determines to which subtype the supertype occurence is related

Subtype Discriminator

( ) are subtypes that contain nonunique subsets of the supertype entity set; that is each entity instance of the supertype may appear in more than one subtype

Overlapping subtypes

The ( ) specifies whether each entity supertype occurrence must also be a member of at least one subtype. The ( ) can be partial or total

Completeness Constraint

(Symbolized by a circle over a single line) means that not every supertype occurrence is a member of a subtype

Partial Completeness

( ) (Symbolized by a circle over a double line) means that every supertype occurrence must be a member of at least one subtype

Total Completeness

( ) is the top-down process of identifying lower-level, more specific entity subtypes from a higher-level entity supertype. ( ) is based on grouping unique characteristics and relationships of the subtypes

Specialization

( ) is the bottom-up process of identifying a higher-level, more generic entity supertype from lower-level entity

Generalization

An ( ) is a "virtual" entity type used to represent multiple entities and relationships in the ERD. An () is formed by combining multiple interrelated entities into a single abstract entity object.

Entity Cluster

A ( ) or ( ) is a real-world, generally accepted identifier used to distinguish--that is uniquely identify -- real-world objects. As its name implies, a () is familiar to end users and forms part of their day-to-day business vocabulary

Natural Key or Natural Identiier

A ( ) is a primary key created by the database designer to simplify the identification of entity instances. The () has no meaning in the user's environment--it exists only to distinguish one entity instane from another

Surrogate Key

() refer to data whose values change over time and for which you must keep a history of the data changes

Time-Variant Data

A ( ) occurs when a relationship is improperly or incompletely identified and is there therefore represented in a way that is not consistent with the real world.

Design Trap

A ( ) occurs when you have one entity in to 1:M relationships to other entities that is not expressed in the model

Fan Trap

( ) is a process for evaluating and correcting table structures to minimize data redundancies, thereby reducing the likelihood of data anomalies. The ( ) process involves assigning attributes to tables based on the concept of determination

Normalization

( ) produces a lower normal form; that is, a 3NF will be converted to a 2NF

Denormalization

( ) exists when there is a functional dependence in which the determinant is only part of the primary key. For example, if (A,B) -> (C,D), B -> C, and (A,B) is the primary key, then the functional dependence B->C is a ( ) because only part of the primary key (B) is needed to determine the value of C.

Partial Dependency

A ( ) exists when there are functional dependencies such as X -> Y, Y -> Z, and X is the primary key

Transitive Dependency

A ( ) derives its name from the fact that a group of multiple entries of the same type can exist

Repeating Group

A ( ) diagram that depicts all dependencies found within a given table structure

Dependency

The term ( ) describes the tabular format in which:

- All of the key attributes are defines

- There are no repeating groups in the table

- Each row/column intersection contains one and only one value, not a set of values

- All atributes are dependent

A ( ) is any attribute whose value dependency, write a copy of its determinant other values within a row

Determinant

A table is in ( ) when:
- It is 2NF
and
- It contains no transitive dependencies

Third Normal Form (3NF)

An ( ) is one that cannot be further subdivided

Atomic Attribute

( ) refers to the level of detail represented by the values stored in a table's row.

Granularity

A table is in ( ) when every determinate in the table is a candidate key.

Boyce-Codd normal form (BCNF)

( ) are a brief, precise and unambiguous description of a policy, procedure, or principle within a specific organization.
- Sometimes misnamed

Business Rules

Anything about which data are to be collected and stored
- Person, Place, Thing, or Event

Within a specialization hierarchy, every subtype can have blank supertype(s) to which it is directly related.

One or More

The property of blank enables an entity subtype to inherit the attributes and relationships of the supertype

Inheritance

The default comparison condition for the subtype discriminator attribute is the blank comparison

Equality

Overlapping subtypes are subtypes that contain ( ) subsets of the supertype entity set

Nonunique

( ) is the bottom-up process of identifying a higher-level, more generic entity supertype from lower-level entity subtypes.

Generalization

An entity cluster is formed by combining multiple interrelated entities into ( )

Single Abstract Entity Object

The ( ) characteristic of a primary key states that: The PK should not have embedded semantic meaning. An attribute with embedded semantic meaning is probably better used as a descriptive characteristic of the entity rather than as an identifier

Nonintelligent

Composite primary keys are particularly useful as identifiers of composite entities, where each primary key is allowed only once in the ( ) relationship.

M:N

Normalization works through a series of stages called normal forms

Normalization is a very important database design ingredient and the highest level is always the most desirable

All relational tables satisfy the 1NF requirements

Converting a database format from 1NF to 2NF is a complex process

It is possible for a table in 2NF to exhbit transitive dependency, where one or more nonprime attributes functionally determine other nonprime attributes

The combination of normalization and ER modeling yields a useful ERD, whose entities my now be translated into appropriate relationship structures

The advantage of higher processing speed must be carefully weighed against the disadvantage of data anomalies

Normalization purity is easy to sustain in the modern database enviroment

Unnormalized database tables often lead to various data redundancy disasters in production databases.

1NF, 2NF, and 3NF are ( )

Some very specialized applications may require normalization beyond the ( )

A relational table must not contain a()

If you have three different transitive dependencies, ( ) different determinant(s) exist

Before converting a table into 3NF, it is imperative that the table already be in ( )

An Atomic attribute ( )

The most likely data type for a surrogate key is ( )

From a strictly database point of view, ( ) attribute values can be calculated when they are needed to write reports or invoices

A table where all attributes are dependent on the primary key and are independent on the primary key and are independent of each other, an no row contains two or more multivalued facts about an entity, is said to be in ( )

When designing a database, you should ( )

Systems analysis is used to determine the need for an information system and to establish to limits

The SDLC's planning phase yields a general overview of the company and its objectives.

Problems defined during the planning phase are examined in greater detail during the analysis phase

During the testing phase, the system is subjected to exhaustive testing until it is ready for use

Because every request for structural changes requires retracing the SDLC steps, the system is always at some stage of the SDLC

To analyze the company situation, the database designer must discover what the company's operational components are, how they interact

The testing and evaluation phase occurs after applications programming

After the initial declarations in a study, the database designer must carefully probe in order to generate additional information that will help define the problem within the larger framework of company operations

The testing and evaluation phase occurs after applications programming

Performance evaluation is rendered more difficult by the fact that there are standard measurements for database performance

Coding, testing, and debugging are part of the ( ) phase of the SDLC

Installation and fine tuning are part of the ( ) phase of the SDLC

Evaluation, maintenance, and enhancement are part of the ( ) phase of the SDLC

The SDLC is most important to the ( )

What are the requirements of the current system's end user? is a question asked during the ( ) phase of the SDLC

Producing the required information flow is part of the ( ) phase of the DBLC

The implementation and loading phase of the DBLC involves ( )

Once the data has been loaded into the database, the ( ) tests and fine-tunes the database for performance, integrity, concurrent access, and security constraints.

The first step in developing the conceptual model using ER diagrams is to ( )

The ( ) design is the process of selecting the data storage data access characteristics of the database.